. Scientific Frontline: Machine learning drives drug repurposing for neuroblastoma

Monday, December 29, 2025

Machine learning drives drug repurposing for neuroblastoma

Daniel Bexell leads the research group in molecular pediatric oncology, and Katarzyna Radke, first author of the study.
Photo Credit: Lund University

Using machine learning and a large volume of data on genes and existing drugs, researchers at Lund University in Sweden have identified a combination of statins and phenothiazines that is particularly promising in the treatment of the aggressive form of neuroblastoma. The results from experimental trials showed slowing of tumor growth and higher survival rates. 

The childhood cancer, neuroblastoma, affects around 15-20 children in Sweden every year. Most of them fell ill before the age of five. Neuroblastoma is characterized by, among other things, tumors that are often resistant to drug treatment, including chemotherapy. The disease exists in both mild and severe forms, and the Lund University researchers are mainly studying the aggressive form, high-risk neuroblastoma. This variant is the form of childhood cancer with the lowest survival rate. 

 Daniel Bexell’s research team has for several years studied which medicines, individually and in combination, could cure or slow down the disease. In a new study, which has been published in EMBO Molecular Medicine, they have specifically examined drugs that have already been approved for other conditions, an approach known as drug repurposing. 

 “This disease has a high relapse risk. Chemotherapy drugs often work well initially, but when the cancer comes back, it’s resistant,” says Daniel Bexell, head of the Molecular Pediatric Oncology research team at Lund University. 

 In the new study, the researchers collaborated with the British AI/biotech company Healx, researchers at Karolinska Institutet, and two childhood cancer charities: the aPODD Foundation, based in the UK, and ENEA (European Neuroblastoma Association), based in Italy. By using machine learning, drugs have been identified that have the potential to be effective against neuroblastoma. A large volume of data on how drugs function has been used along with knowledge on genes that are specifically relevant to neuroblastoma.  

 Using this information, the Lund University researchers test the drugs on aggressive neuroblastoma tumors that come from patients. The drugs were first tested individually and then in combination. 

 “We quickly noted that two types of drugs could have an effect individually. But together the effect was very powerful – a strong synergy,” says Katarzyna Radke, formerly a doctoral student in the research team and first author of the study. 

 The drugs were a lipid-lowering statin and a phenothiazine, a drug used in the treatment of migraine and nausea, among others. 

 It was previously known that statins impede the new formation of cholesterol. The researchers now saw that phenothiazine also lowered cholesterol levels, but in another complementary way.  

 “Together, this led to low cholesterol levels in the tumor cells. Many tumor cells died, and those that survived were sensitive to chemotherapy drugs. We knew that cholesterol was important for the tumor, but were surprised that it had such strong effects,” says Daniel Bexell. 

 In laboratory trials, this drug combination could impede tumor growth and improve survival rates among mice. Now further studies are needed to enhance the chemical properties of the two drugs to optimize the effect.  

 “However, in our trials the treatment looks very promising, even for resistant tumors, says Daniel Bexell. 

Funding: The aPODD Foundation, ENEA (European Neuroblastoma Association), Healx, Crafoord Foundation, the Swedish Cancer Society, the Swedish Childhood Cancer Fund and the Swedish Research Council.

Published in journal: EMBO Molecular Medicine

TitleRepurposing statins and phenothiazines to treat chemoresistant neuroblastoma

Authors: Katarzyna Radke, Kristina Aaltonen, Erick A Muciño-Olmos, Javanshir Esfandyari, Aleksandra Adamska, Joachim T Siaw, Dora Adamic, Chiara Lago, Adriana Mañas, Alexandra Seger, Karin Hansson, Oksana Rogova, Sophie Lehn, Daniel J Mason, Daniel J O’Donovan, Ian Roberts, Antonia Lock, Jane Brennan, Kristian Pietras, Emma J Davies, Peter Spégel, Oscar C Bedoya-Reina, David Brown, Neil T Thompson, Cesare Spadoni, and Daniel Bexell

Source/CreditLund University | Erika Svantesson

Reference Number: ms122925_01

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